Foundation models for physiological data, how to develop them, and what to expect of them
Abstract
The advance of a new generation arti fi cial intelligence ( AI ) models is accelerating. Their appearance in the public spotlight started with the release of OpenAI ’ s ChatGPT web application driven by a large language model — generative pretrained transformer ( GPT 3.0 ) in November 2022. Since then, even more advanced and diverse large language models have been released such as GPT 4 from OpenAI, LlaMA from Meta, and Claude from Anthropic, just to name a few. In parallel to these large models for languages, models of similar architectures for different data modalities including images, audio, and video have been developed, and have demonstrated impressive performance in various domains at a performance level that could not have been imagined before the release of ChatGPT in 2022. The most recent achievement in this regard was Google ’ s Gemini released in December 2023. The speed at which these models are released and the new levels of capacities they demonstrate are astonishing and have triggered society-wide discussions of issues such as AI safety. An executive order on AI was issued by the US government in November symbolizing the importance and urgency in addressing these issues.
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